Senior Data Engineer

Foley is a modern SaaS company focused on reimagining how safety-sensitive industries hire, stay compliant, and manage risk. They are seeking a Senior Data Engineer to design, build, and scale data systems, ensuring reliable data pipelines and contributing to enterprise data architecture. The role involves partnering with cross-functional teams to deliver scalable, trusted data solutions that support decision-making across the company.

Responsibilities:

• Design, build, and maintain scalable data pipelines across internal databases, vendor systems, and our data warehouse
• Support both batch and event-driven or CDC-based data workflows
• Improve pipeline reliability, observability, and performance
• Troubleshoot issues in production and proactively solve data quality or system problems
• Build and maintain data warehouse schemas and transformation layers to support analytics and operational use cases
• Contribute to data modeling standards and best practices
• Implement data governance practices, including role-based access control and trusted data definitions
• Support data quality and consistency across systems
• Partner with Engineering, Product, Analytics, and business stakeholders to translate requirements into practical data solutions
• Communicate clearly about implementation choices, tradeoffs, and technical constraints
• Help stakeholders access data that is reliable, understandable, and useful
• Identify opportunities to improve data workflows through better tooling, automation, and engineering practices
• Embrace new technologies, including AI-enabled tools, where they improve quality or efficiency
• Continuously improve system design, maintainability, and team effectiveness
• Contribute to the design and evolution of our enterprise data architecture
• Help shape scalable patterns for how data is ingested, transformed, stored, and accessed
• Apply sound architectural judgment to build solutions that balance scalability, maintainability, and performance
• Support a layered data architecture, including bronze, silver, and gold data models

Requirements:

• Strong experience building and maintaining ETL/ELT pipelines in production environments
• Experience working across both batch and streaming / CDC / event-driven data patterns
• Proven ability to design and maintain scalable warehouse schemas and data models within a layered architecture
• Strong experience with Python, SQL, and cloud-based data platforms
• Experience with AWS data services such as Redshift, Glue, Lambda, S3, and EventBridge
• Strong software engineering fundamentals, including reliability, testing, and maintainability
• Ability to operate independently and deliver high-quality solutions within a defined technical scope
• Strong problem-solving skills and a track record of handling issues in production environments
• Experience with medallion architecture and bronze, silver, gold data modeling patterns
• Experience with graph data models and entity resolution
• Experience implementing data governance practices, including RBAC
• Experience supporting machine learning or LLM-related pipelines in production environments
• Familiarity with tools or workflows that use AI to improve engineering productivity
• Experience partnering with Data Science or Analytics teams to support data products